Servidores MCP

El registro abierto de servidores Model Context Protocol. Encuentra herramientas, recursos y prompts para tus agentes de IA, filtrados por categoría, transporte o caso de uso.

Servidores

177

Herramientas

471

Categorías

11

Colaboradores

155

12 servidores

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SQLite MCP ServerAnthropic

MCP server for SQLite database interaction and business intelligence. Enables AI agents to query SQLite databases, create and modify tables, run analytical queries, and generate insights from data. Supports read-write operations with transaction safety and provides schema introspection for understanding database structure.

86.2k
ClickHouse MCP ServerClickHouse

Provides AI agents with access to ClickHouse analytical databases through the Model Context Protocol. Enables running analytical queries, exploring table schemas, inspecting materialized views, and monitoring query performance. Designed for OLAP workloads with support for large result sets and query profiling.

1.6k
BigQuery MCP ServerGoogle Cloud Community

MCP server for Google BigQuery that lets AI agents explore datasets, inspect table schemas, and run SQL analytics queries with dry-run cost estimation. Useful for natural-language data analysis, ad-hoc reporting, and pipeline debugging against large-scale BigQuery warehouses.

1.5k
Snowflake MCP ServerSnowflake

Official Snowflake MCP server enabling AI agents to query and analyze data in the Snowflake AI Data Cloud. Supports running SQL against warehouses, exploring databases and schemas, describing tables, and invoking Cortex AI services for search and analytics, with role-based access control honored end to end.

980
DuckDB MCP ServerMotherDuck

MCP server for DuckDB, the fast in-process analytical database. Lets AI agents run analytical SQL over local files (CSV, Parquet, JSON), attach databases, inspect schemas, and profile queries. Ideal for ad-hoc data analysis, ETL prototyping, and querying large columnar files without a separate database server.

780
Elasticsearch MCP ServerElastic

Official Elastic MCP server that connects AI agents to Elasticsearch data using the Model Context Protocol. Enables natural language interactions with Elasticsearch indices — querying, analyzing, and retrieving data without custom APIs. Supports both stdio and streamable-HTTP transports, and works with Elasticsearch 8.x/9.x clusters including Elasticsearch Serverless. Distributed as a Docker container image from the Elastic registry.

320
Apache Doris MCP ServerApache Doris

Apache Doris' MCP server provides agents with governed access to Doris analytics databases for schema discovery, query assistance, and operational investigation.

0
Fivetran MCP ServerFivetran

Fivetran's MCP server helps agents inspect data connectors and sync health, diagnose broken connections, and answer operational questions about managed ELT pipelines.

0
Metabase MCP ServerMetabase

Metabase's built-in MCP server that lets AI clients connect directly to a Metabase instance, scoped to the connecting user's permissions. Enables agents to discover databases and models, run queries, and retrieve results and dashboards so teams can ask questions of their business intelligence data in natural language.

0
MotherDuck MCP ServerMotherDuck

Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.

0
Tinybird MCP ServerTinybird

MCP server for interacting with a Tinybird Workspace from any MCP client. Lets AI agents explore data sources, call published API endpoints, run SQL queries over real-time data, and push datafiles, making Tinybird's analytics readily available to LLM-driven workflows.

0
dbt MCP Serverdbt Labs

Official dbt Labs MCP server for analytics engineering workflows. Lets AI agents run dbt commands (build, run, test), inspect models and lineage via the dbt project, and query the Semantic Layer and Discovery API in dbt Cloud. Useful for transforming data, validating models, and answering metric questions grounded in governed definitions.

640

Skills frente a servidores MCP

¿cuál es la diferencia?

Skillsel «qué hacer»

Una Skill reúne conocimientos prácticos —instrucciones, un prompt de ejemplo y modelos recomendados— para que un agente realice una tarea de forma consistente. Las Skills aportan conocimiento, no nuevas conexiones.

Servidores MCPel «cómo conectarse»

Un servidor MCP proporciona nuevas capacidades a un agente conectándolo con sistemas reales —bases de datos, API o archivos— mediante un transporte. MCP añade conexiones y acciones, no instrucciones de tarea.

Regla práctica: usa una Skill cuando necesites que el modelo realice bien una tarea y un servidor MCP cuando necesites conectarlo con una herramienta o sistema. Se complementan: una Skill puede utilizar las herramientas que proporciona un servidor MCP.

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